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This is a list of statistical procedures which can be used for the analysis of categorical data, also known as data on the nominal scale and as categorical variables. General tests [ edit ]
This is the aim of multiple factor analysis which balances the different issues (i.e. the different groups of variables) within a global analysis and provides, beyond the classical results of factorial analysis (mainly graphics of individuals and of categories), several results (indicators and graphics) specific of the group structure.
Shakespeare has been known as "the Bard" since the eighteenth century. [2] One who idolizes Shakespeare is known as a bardolator. The term bardolatry , derived from Shakespeare's sobriquet "the Bard of Avon" and the Greek word latria "worship" (as in idolatry , worship of idols ), was coined by George Bernard Shaw in the preface to his ...
Engraving of Shakespeare: the term "bardolatry" derives from Shaw's coinage "Bardolator", combining the words "bard" and "idolatry" by refers to the excessive adulation of Shakespeare. [1] This article is a collection of quotations and other comments on English playwright William Shakespeare and his works.
Standard for structuring data such that "each variable is a column, each observation is a row, and each type of observational unit is a table". It is equivalent to Codd's third normal form. [4] time domain time series time series analysis time series forecasting treatments Variables in a statistical study that are conceptually manipulable.
HuffPost Data Visualization, analysis, interactive maps and real-time graphics. Browse, copy and fork our open-source software. Remix thousands of aggregated polling results. Keep up with our latest on Twitter and Tumblr. Special Elections
“For example, ‘I hope your test went well. I know you studied hard for that,’ or ‘What a beautiful day today. I hope you had fun at recess.’” ...
Data mining is a particular data analysis technique that focuses on statistical modeling and knowledge discovery for predictive rather than purely descriptive purposes, while business intelligence covers data analysis that relies heavily on aggregation, focusing mainly on business information. [4]